Digital Curation & Digital Preservation – Page 3

"To Share or Not to Share? Image Data Sharing in the Social Sciences and Humanities"

Introduction. The paper aims to investigate image data sharing within social science and humanities. While data sharing is encouraged as a part of the open science movement, little is known about the approaches and factors influencing the sharing of image data. This information is evident as the use of image data in these fields of research is increasing, and data sharing is context dependent. . . .

Results. The findings show that image data sharing is not an established research practice, and when it happens it is mostly done via informal means by sharing data through personal contacts. Supporting the scientific community, the open science agenda and fulfilling research funders’ requirements motivate scholars to share their data. Impeding factors relate to the qualities of data, ownership of data, data stewardship, and research integrity.

https://tinyurl.com/nt8md9cj

"DMPs as Management Tool for Intellectual Assets by SMART-metrics"

Data Management Plans (DMPs) are vital components of effective research data management (RDM). They serve not only as organisational tools but also as a structured framework dictating the collection, processing, sharing/publishing, and management of data throughout the research data life cycle. This can include existing data curation standards, the establishment of data handling protocols, and the creation, when necessary, of community curation policies. Therefore, DMPs present a unique opportunity to harmonise project management efforts for optimising the formulation and execution of project objectives.

To harness the full potential of DMPs as project management tools, the SMART approach (i.e., Specific, Measurable, Achievable, Relevant, and Time-bound) emerges as a compelling methodology. During the initial stage of the project proposal, drafted SMART metrics can offer a systematic approach to map work packages (WPs) and deliverables to the overarching project objectives. Then, the Principal Investigators (PIs) can ensure the consortia that all the project potential intellectual assets (i.e., expected research results) were considered properly, as well as their necessary timelines, resources, and execution. It becomes imperative for data stewards (DSs) and governance policymakers to educate and provide guidelines to researchers on the advantages of developing well-curated DMPs that align results with SMART metrics. This alignment ensures that every intellectual asset intended as a research result (e.g., intellectual properties, publications, datasets, and software) within the project is subject to rigorous drafted planning, execution, and accountability.

Consequently, the risk of unforeseen setbacks and/or deviations from the original objectives is minimised, increasing the traceability and transparency of the research data life cycle. In addition, the integration of Technology Readiness Levels (TRLs) into this proposed enhanced DMP provides a systematic method to evaluate the maturity and readiness of technologies across scientific disciplines. Regular TRL assessments will allow PIs: (1) to monitor the WP progress, (2) to adapt research strategies if required, and (3) to ensure the projects remain in line with the drafted SMART metrics in the enhanced DMP before the project started. The TRLs can also help PIs maintain their focus on project milestones and specific tasks aligned with the original objectives, contributing to the overall success of their endeavours, while improving the transparency for the reporting and divulgation of the research results.

The paper presents the overall framework for enhancing DMPs as project management tools for any intellectual assets using SMART metrics and TRLs, as well as introducing suggested support services for data stewardship teams to assist PIs when implementing this novel framework effectively.

https://tinyurl.com/25ymtyyk

"Biomedical Data Repository Concepts and Management Principles"

The demand for open data and open science is on the rise, fueled by expectations from the scientific community, calls to increase transparency and reproducibility in research findings, and developments such as the Final Data Management and Sharing Policy from the U.S. National Institutes of Health and a memorandum on increasing public access to federally funded research, issued by the U.S. Office of Science and Technology Policy. This paper explores the pivotal role of data repositories in biomedical research and open science, emphasizing their importance in managing, preserving, and sharing research data. Our objective is to familiarize readers with the functions of data repositories, set expectations for their services, and provide an overview of methods to evaluate their capabilities. The paper serves to introduce fundamental concepts and community-based guiding principles and aims to equip researchers, repository operators, funders, and policymakers with the knowledge to select appropriate repositories for their data management and sharing needs and foster a foundation for the open sharing and preservation of research data.

https://doi.org/10.1038/s41597-024-03449-z

"Understanding the Value of Curation: A Survey of Us Data Repository Curation Practices and Perceptions"

Data curators play an important role in assessing data quality and take actions that may ultimately lead to better, more valuable data products. This study explores the curation practices of data curators working within US-based data repositories. We performed a survey in January 2021 to benchmark the levels of curation performed by repositories and assess the perceived value and impact of curation on the data sharing process. Our analysis included 95 responses from 59 unique data repositories. Respondents primarily were professionals working within repositories and examined curation performed within a repository setting. A majority 72.6% of respondents reported that "data-level" curation was performed by their repository and around half reported their repository took steps to ensure interoperability and reproducibility of their repository’s datasets. Curation actions most frequently reported include checking for duplicate files, reviewing documentation, reviewing metadata, minting persistent identifiers, and checking for corrupt/broken files. The most "value-add" curation action across generalist, institutional, and disciplinary repository respondents was related to reviewing and enhancing documentation. Respondents reported high perceived impact of curation by their repositories on specific data sharing outcomes including usability, findability, understandability, and accessibility of deposited datasets; respondents associated with disciplinary repositories tended to perceive higher impact on most outcomes. Most survey participants strongly agreed that data curation by the repository adds value to the data sharing process and that it outweighs the effort and cost. We found some differences between institutional and disciplinary repositories, both in the reported frequency of specific curation actions as well as the perceived impact of data curation. Interestingly, we also found variation in the perceptions of those working within the same repository regarding the level and frequency of curation actions performed, which exemplifies the complexity of a repository curation work. Our results suggest data curation may be better understood in terms of specific curation actions and outcomes than broadly defined curation levels and that more research is needed to understand the resource implications of performing these activities. We share these results to provide a more nuanced view of curation, and how curation impacts the broader data lifecycle and data sharing behaviors.

https://doi.org/10.1371/journal.pone.0301171

"The Student Staffing Advantage: Data Science Consulting Service at NC State University Libraries"

The primarily peer-to-peer, graduate student-staffed Data Science Consulting Service at NC State University Libraries, within the Data & Visualization Services (DVS) department and collaborating closely with the Data Science Academy (DSA), has established a sustainable service and staffing model focused on providing broad data science analytic support to researchers across the university community. The service addresses the needs of university researchers who possess domain knowledge in their fields of study but a skills gap in the data science competencies required for research. The literature shows that it has been difficult for libraries to cover these needs with existing staffing models. Few universities follow the model practiced at NC State University, so a scan of the current landscape of data science consulting at universities across the country was performed to establish context. The support model and its advantages are described, including partnership with the DSA, student success, model sustainability and future directions for the service. Through a summary of the DVS assessment and needs evaluation process, the service’s advantages in staying ahead of patron needs are illustrated. This scalable, sustainable, student-focused model could be implemented by similar research institutions to expand the capacity of their technical research services.

https://onlinelibrary.wiley.com/doi/10.1002/sta4.702

Paywall: "Journal Requirement for Data Sharing Statements in Clinical Trials: A Cross-Sectional Study"

Despite ICMJE [International Committee of Medical Journal Editors] recommendations, more than 27% of biomedical journals do not require clinical trials to include data sharing statements, highlighting room for improved transparency.

https://doi.org/10.1016/j.jclinepi.2024.111405

"The NIH Data Management and Sharing Policy for Non-data librarians" (Video)

The NIH Data Management and Sharing (DMS) Policy went into effect early last year. That means that the policy that so many medical data librarians have been talking about is finally in place and affecting researchers. Libraries do not need a data expert or an institutional repository to get started with supporting NIH grants with this new policy. Reference interviewing skills and a basic knowledge of the NIH DMS Plan format can be combined to walk researchers through the basics. In this session, librarians who are new to the NIH DMS Policy will learn the essentials: what is the NIH DMS policy, who is affected, and how do researchers incorporate it into an NIH grant application.

https://www.youtube.com/watch?v=6JAj5rHpFd0

"Maggot: An Ecosystem for Sharing Metadata within the Web of Fair Data"

We developed Maggot which stands for Metadata Aggregation on Data Storage, specifically designed to annotate datasets by generating metadata files to be linked into storage spaces. Maggot enables users to seamlessly generate and attach comprehensible metadata to datasets within a collaborative environment. This approach seamlessly integrates into a data management plan, effectively tackling challenges related to data organisation, documentation, storage, and frictionless FAIR metadata sharing within the collaborative group and beyond. Furthermore, for enabling metadata crosswalk, metadata generated with Maggot can be converted for a specific data repository or configured to be exported into a suitable format for data harvesting by third-party applications.

https://doi.org/10.1101/2024.05.24.595703

"Narrowing the Lens: Preservation Assessment for Digital Manuscripts"

As a response to Ben Goldman’s 2011 call to action in RBM regarding born-digital manuscripts, this article revisits the topic thirteen years later. Drawing inspiration from Goldman’s work at the University of Wyoming, the authors attempt to narrow the preservation lens further by focusing on specific collections and considering factors like file types, risk, and resource availability. The authors suggest further humble, but practical, steps towards preserving born-digital materials, based on their experiences and while emphasizing the importance of contextual decision-making in the face of complex challenges.

https://tinyurl.com/yp4352mr

"Rethinking Data Management Planning: Introducing Research Output Management Planning (ROMPi) Approach"

Data management plans (DMPs), designed to adhere to Findable, Accessible, Interoperable, Reusable (FAIR) principles, were introduced to enhance research data management (RDM) but have encountered challenges in implementation. This essay calls for a paradigm shift by introducing the ‘Research Output Management Planning (ROMPi)’ approach, aiming to integrate traditional research project management practices promoting a holistic perspective of RDM. In its essence, ROMPi reframes the DMP in the conventional project management work breakdown structure in work packages (WPs), with research outputs going through their lifecycle. It also advocates reimagining the concept of data into research outputs, acknowledging a holistic perspective of the research outcomes. We demonstrated that the research project management perspective at the early implementation stage could ultimately align DMP within the research process. ROMPi offers a practical research output management approach, fostering a holistic project-researcher-centric perspective.

https://doi.org/10.5334/dsj-2024-034

"The FAIR Assessment Conundrum: Reflections on Tools and Metrics"

Several tools for assessing FAIRness have been developed. Although their purpose is common, they use different assessment techniques, they are designed to work with diverse research products, and they are applied in specific scientific disciplines. It is thus inevitable that they perform the assessment using different metrics. This paper provides an overview of the actual FAIR assessment tools and metrics landscape to highlight the challenges characterising this task. In particular, 20 relevant FAIR assessment tools and 1180 relevant metrics were identified and analysed concerning (i) the tool’s distinguishing aspects and their trends, (ii) the gaps between the metric intents and the FAIR principles, (iii) the discrepancies between the declared intent of the metrics and the actual aspects assessed, including the most recurring issues, (iv) the technologies used or mentioned the most in the assessment metrics. The findings highlight (a) the distinguishing characteristics of the tools and the emergence of trends over time concerning those characteristics, (b) the identification of gaps at both metric and tool levels, (c) discrepancies observed in 345 metrics between their declared intent and the actual aspects assessed, pointing at several recurring issues, and (d) the variety in the technology used for the assessments, the majority of which can be ascribed to linked data solutions. This work also highlights some open issues that FAIR assessment still needs to address.

https://doi.org/10.5334/dsj-2024-033

"Data Competency for Academic Librarians: Evaluating Present Trends and Future Prospects"

This paper reports an investigation into the perception of academic librarians on data competency in their daily roles across various library departments in the United States and Canada. . . . The findings reveal a complex engagement pattern with data tasks, with librarians in data-specific roles dedicating a considerable portion of their work to these activities, while the majority engage less frequently, indicating that data tasks are a minor part of their overall responsibilities. . . . Our study identifies a crucial need for improved competencies in data management and collection development. . . Additionally, our findings reveal a critical gap between academic libraries’ demand for data skills and the content coverage in MLIS programs, emphasizing the need for curriculum updates to prepare librarians for the evolving information landscape.

https://doi.org/10.1016/j.acalib.2024.102897

"The Global Lens: Highlighting National Nuances in Researchers’ Attitudes to Open Data"

This report investigates the variations seen in researcher’s attitudes towards open data across Ethiopia, Japan and the United States, using responses from the State of Open Data surveys. Highlighting: what open data is and its importance towards global scientific advancement, outlining methods that were used, outward context and overall suggestions towards policy makers.

Ethiopia and Japan were found to display contrasting responses, with the United States often representing the middle ground. Researchers in Ethiopia show the highest familiarity with FAIR principles (36.50%), support for a national open data mandate (76.96%), and agreement with penalising non-compliance (56.74%). In contrast, Japan has the lowest familiarity with FAIR principles (10.20%), support for a national mandate (41.86%), and agreement with penalties (35.78%). The United States falls in between, with 37.60% familiarity with FAIR principles, 61.22% supporting a national mandate, and 54.09% supporting penalties.

The factors shaping these attitudes, including funding policies, research culture, and individualistic behaviours have also been examined. Recommendations suggest Ethiopia could leverage its strong support by establishing clear national policies, the United States could build on existing federal policies, and Japan may need a more gradual approach, engaging researchers in policy development.

https://tinyurl.com/45xsvc8h

"Challenges and Roadblocks to Robust Metadata in the Scholarly Communications Industry"

For the scholarly communications community to extract the most value from scientific research, as well as to successfully move from subscription to open access publishing models, it is essential to have ‘clean’ metadata and a robust infrastructure to build the required workflows, processes and systems to support effective use of that metadata. The obstacles to achieving a supporting infrastructure and implementing effective workflows are many, negatively impacting every stakeholder group and every aspect of the research and publishing process.

https://doi.org/10.1629/uksg.642

Paywall: "Job Advertisements for Data Visualization in Academic Libraries: A Content Analysis of Job Postings"

The objectives of this study are: i) to identify the responsibilities that professionals working in the DV field are expected to undertake, and ii) to analyze the current stated qualifications and competencies required for DV-related positions.. . . The findings indicated that library professionals in the field of DV are increasingly tasked with a broader spectrum of responsibilities and duties, with a pronounced preference for those demonstrating expertise in cross-disciplinary domains and possessing exceptional general competencies, in addition to the requisite professional qualifications and skills, such as interdisciplinary liaison and commitment to equity and diversity..

https://doi.org/10.1016/j.acalib.2024.102896

Pew Research Center: When Online Content Disappears

A quarter of all webpages that existed at one point between 2013 and 2023 are no longer accessible, as of October 2023. In most cases, this is because an individual page was deleted or removed on an otherwise functional website.

For older content, this trend is even starker. Some 38% of webpages that existed in 2013 are not available today, compared with 8% of pages that existed in 2023. . . .

Nearly one-in-five tweets are no longer publicly visible on the site just months after being posted.

https://tinyurl.com/bdh4c6xh

"Re-Use of Research Data in the Social Sciences. Use and Users of Digital Data Archive"

The aim of this paper is to investigate the re-use of research data deposited in digital data archive in the social sciences. The study examines the quantity, type, and purpose of data downloads by analyzing enriched user log data collected from Swiss data archive. The findings show that quantitative datasets are downloaded increasingly from the digital archive and that downloads focus heavily on a small share of the datasets. The most frequently downloaded datasets are survey datasets collected by research organizations offering possibilities for longitudinal studies. Users typically download only one dataset, but a group of heavy downloaders form a remarkable share of all downloads. The main user group downloading data from the archive are students who use the data in their studies. Furthermore, datasets downloaded for research purposes often, but not always, serve to be used in scholarly publications. Enriched log data from data archives offer an interesting macro level perspective on the use and users of the services and help understanding the increasing role of repositories in the social sciences. The study provides insights into the potential of collecting and using log data for studying and evaluating data archive use.

https://doi.org/10.1371/journal.pone.0303190

"Factors Influencing Perceptions of Trust in Data Infrastructures"

Trust is an essential pre-condition for the acceptance of digital infrastructures and services. Transparency has been identified as one mechanism for increasing trustworthiness. Yet, it is difficult to assess to which extent and how exactly different aspects of transparency contribute to trust, or potentially impede it in cases of overwhelming complexity of the information provided. To address these issues, we performed two initial studies to help determining the factors that influence or have impact on trust, focusing on transparency across a range of elements associated with data, data infrastructures and virtual research environments. On one hand, we performed a survey among IT experts in the field of data science focusing on quality aspects in the context of re-using and sharing open source software, assessing issues such as the need for documentation, test cases, and accountability. On the other hand, we complemented this with a set of semi-structured interviews with senior researchers to address specific issues of the degree of transparency achievable with different approaches. They include, for example, the amount of transparency we can achieve with approaches from explainable AI, or the usefulness and limitations of data provenance in determining the suitability of data for reuse and others. Specifically, we consider mechanisms on three levels, i.e. technical, process-oriented as well as social mechanisms. Starting from attributes of trust in the "analogue world", we aim to understand which of these can be applied in the digital world, how they differ, and what additional mechanisms need to be established, in order to support trust in complex socio-technological processes and their emergent results when the traditional approaches cannot be applied anymore.

https://doi.org/10.2218/ijdc.v18i1.921

"Research Data Management in the Humanities: Challenges and Opportunities in the Canadian Context"

In recent years, research funders across the world have implemented mandates for research data management (RDM) that introduce new obligations for researchers seeking funding. Although data work is not new in the humanities, digital research infrastructures, best practices, and the development of highly qualified personnel to support humanist researchers are all still nascent. Responding to these changes, this article offers four contributions to how humanists can consider the role of "data" in their research and succeed in its management. First, we define RDM and data management plans (DMP) and raise some exigent questions regarding their development and maintenance. Second, acknowledging the unsettled status of "data" in the humanities, we offer some conceptual explanations of what data are, and gesture to some ways in which humanists are already (and have always been) engaged in data work. Third, we argue that data work requires conscious design—attention to how data are produced—and that thinking of data work as involving design (e.g., experimental and interpretive work) can help humanists engage more fruitfully in RDM. Fourth, we argue that RDM (and data work, generally) is labour that requires compensation in the form of funding, support, and tools, as well as accreditation and recognition that incentivizes researchers to make RDM an integral part of their research. Finally, we offer a set of concrete recommendations to support humanist RDM in the Canadian context.

https://doi.org/10.16995/dscn.9956

"Recognising Open Research Data in Research Assessment: Overview of Practices and Challenges"

The literature review aims at identifying content and key issues regarding the assessment of ORD practices nationally and internationally. It starts from the observation that research assessment needs to be reformed as they are currently biased towards scientific publications. Internationally, discussions and projects thereon have emerged. To contextualise recORD and this literature review, we first describe international and Swiss initiatives for reforming research assessment and how they include ORD recognition. The remainder of the review follows an innovative methodology as it identifies first core values in responsible research assessment, and second existing frameworks, to thirdly derive propositions to keep in mind when developing concrete ORD-specific research assessment recommendations. In a final section, the review presents further readings and useful weblinks on the recognition of ORD in research assessment.

https://zenodo.org/doi/10.5281/zenodo.11060206

"The Products and Multi-Disciplinarity of Data-Centric Tasks: Influences on Data Searchers’ Behaviors and Cognition"

The study sought to answer the following research questions:

RQ 1: How do data-centric tasks with different products and levels of multi-disciplinarity affect data search behaviors?

RQ 2: How do data-centric tasks with different products and levels of multi-disciplinarity affect the utilization of different cognitive systems?

https://doi.org/10.1016/j.lisr.2024.101302

"An Analysis of the Effects of Sharing Research Data, Code, and Preprints on Citations"

In this study, we investigate whether adopting one or more Open Science practices leads to significantly higher citations for an associated publication, which is one form of academic impact. We use a novel dataset known as Open Science Indicators, produced by PLOS and DataSeer, which includes all PLOS publications from 2018 to 2023 as well as a comparison group sampled from the PMC Open Access Subset. In total, we analyze circa 122’000 publications. We calculate publication and author-level citation indicators and use a broad set of control variables to isolate the effect of Open Science Indicators on received citations. We show that Open Science practices are adopted to different degrees across scientific disciplines. We find that the early release of a publication as a preprint correlates with a significant positive citation advantage of about 20.2% on average. We also find that sharing data in an online repository correlates with a smaller yet still positive citation advantage of 4.3% on average. However, we do not find a significant citation advantage for sharing code.

https://arxiv.org/abs/2404.16171

"Health Data Sharing Attitudes Towards Primary and Secondary Use of Data: A Systematic Review"

Of 2109 studies identified through our search, 116 were included in the qualitative synthesis, yielding a total of 228,501 participants and various types of HD represented: person-generated HD (n = 17 studies and 10,771 participants), personal HD in general (n = 69 studies and 117,054 participants), Biobank data (n = 7 studies and 27,073 participants), genomic data (n = 13 studies and 54,716 participants), and miscellaneous data (n = 10 studies and 18,887 participants). The majority of studies had a moderate level of quality (83 [71.6%] of 116 studies), but varying levels of quality were observed across the included studies. Overall, studies suggest that sharing intentions for primary purposes were observed to be high regardless of data type, and it was higher than sharing intentions for secondary purposes. Sharing for secondary purposes yielded variable findings, where both the highest and the lowest intention rates were observed in the case of studies that explored sharing biobank data (98% and 10%, respectively). Several influencing factors on sharing intentions were identified, such as the type of data recipient, data, consent. Further, concerns related to data sharing that were found to be mutual for all data types included privacy, security, and data access/control, while the perceived benefits included those related to improvements in healthcare. Findings regarding attitudes towards sharing varied significantly across sociodemographic factors and depended on data type and type of use. In most cases, these findings were derived from single studies and therefore warrant confirmations from additional studies. . ..

Sharing health data is a complex issue that is influenced by various factors (the type of health data, the intended use, the data recipient, among others) and these insights could be used to overcome barriers, address people’s concerns, and focus on spreading awareness about the data sharing process and benefits.

https://doi.org/10.1016/j.eclinm.2024.102551

"Seek and You May (Not) Find: A Multi-Institutional Analysis of Where Research Data Are Shared"

Research data sharing has become an expected component of scientific research and scholarly publishing practice over the last few decades, due in part to requirements for federally funded research. As part of a larger effort to better understand the workflows and costs of public access to research data, this project conducted a high-level analysis of where academic research data is most frequently shared. To do this, we leveraged the DataCite and Crossref application programming interfaces (APIs) in search of Publisher field elements demonstrating which data repositories were utilized by researchers from six academic research institutions between 2012–2022. In addition, we also ran a preliminary analysis of the quality of the metadata associated with these published datasets, comparing the extent to which information was missing from metadata fields deemed important for public access to research data. Results show that the top 10 publishers accounted for 89.0% to 99.8% of the datasets connected with the institutions in our study. Known data repositories, including institutional data repositories hosted by those institutions, were initially lacking from our sample due to varying metadata standards and practices. We conclude that the metadata quality landscape for published research datasets is uneven; key information, such as author affiliation, is often incomplete or missing from source data repositories and aggregators. To enhance the findability, interoperability, accessibility, and reusability (FAIRness) of research data, we provide a set of concrete recommendations that repositories and data authors can take to improve scholarly metadata associated with shared datasets.

https://doi.org/10.1371/journal.pone.0302426

"Data Services at the Academic Library: A Natural History of Horses and Unicorns"

Methods: We used a web-based inventory of 25 academic libraries at U.S. Research 1 (R1) Carnegie institutions to assess the state of data services at university libraries. We categorized and quantified services, and tested for an effect of library resourcing on the size of library data service portfolios.

Results: Support for data management and geospatial services was relatively widespread, with increasing support in areas of data analyses and data visualization. There was significant variation among services in the modality in which they were offered (web, consult, instruction) and library resourcing had a significant effect on the number of data services a library offered.

https://doi.org/10.7191/jeslib.780